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Sales Enablement & Knowledge

Engagement Knowledge Base Builder

ai

Periodically ingests the engagement corpus—proposals, won deals, delivered work, notes, activities—then classifies and links each artifact by client, sector, problem, and solution to build a searchable index of prior work.

Sales / Revenue OperationsAccount Executive
100%
Of engagement corpus classified and linked
6x
Faster retrieval of relevant prior work
Searchable
Index refreshed on a periodic run
One run, end to end

Refresh run due. Index now ready.

See the knowledge base builder take this quarter's run from a scheduled refresh to an updated index.

Run KB-0412

Periodic corpus ingest · This quarter's work

  • AI
  • 6x faster retrieval
  1. Intake
  2. Organize
  3. Classify
  4. Deliver

01 · Intake

Refresh triggered

Scheduled run opened for this quarter's work

New case

Run open
Run
Periodic corpus ingest · Scheduled refresh
Scope
This quarter's work
Request
Classify, link and index each artifact · Report what was processed and skipped
Case packet · 2 sourcesComplete

Incoming

  • CRMNotes, activities, workstreams, opportunities, accountsReceived
  • Knowledge storeProposals, won deals and delivered workReceived

02 · Organize

Corpus pulled in

CRM records and stored documents gathered for the run

Pulled together

Ingest done
  • CRM records ingestedNotes, activities, workstreams, opportunities and accounts
  • Documents pulledProposals, won deals and delivered work from the knowledge store
  • Artifacts lined upEach artifact queued for typing and extraction

Artifact record

Type
Won-deal proposal
Links
Client, sector, problem, solution
Summary
Generated
Index
Ready to add

03 · Classify

Artifacts classified

Each artifact typed, tagged and summarized from content

Checks applied

Classified
  • Type assignedProposal, won deal, delivered work, note or activityKnowledge store
  • Entities extractedClient, sector, problem and solution per artifactCRM accounts
  • Content supports a tagUntitled exports and scanned PDFs have no extractable textDocument text
Deciding finding

38 left out, not forced

These artifacts had no content to support a tag, so each was logged with its reason.

Unclassified set

Untitled exports
Logged, excluded
Scanned PDFs
No extractable text
Index
Not tagged

04 · Deliver

Index updated

Searchable index built, with a report of skipped items

Run complete

1,284 artifacts indexed

Artifacts are linked by client, sector, problem and solution. 38 without supportable content were logged, not tagged.

Engagements
213
Eligible corpus
About 94%
Unclassified
38 · Logged

Searchable index

Refreshed

Knowledge Base / Vector Index

Next step

Text extraction

Offered for scanned PDFs

Audit trail

  1. CRM and knowledge store ingested09:00
  2. Artifacts classified and linked09:14
  3. 38 unclassified items loggedReason recorded09:31
  4. Index built, report sentKnowledge Base / Vector Index09:38

6x faster retrieval of relevant prior work

Illustrative case · sample data

Use Case 1

Periodic Corpus Ingest

Trigger: Scheduled knowledge base refresh

1.Ingest notes, activities, workstreams, opportunities, and accounts
2.Pull documents from the knowledge store
3.Classify each artifact by type
4.Extract client, sector, problem, and solution
5.Generate a searchable summary per artifact
6.Build and update the index
7.Report processed counts and unclassified items
✓

The firm's historical work becomes a structured, searchable asset instead of scattered files.

Use Case 2

Classification Quality Control

Trigger: Artifacts can't be classified from their content

1.Detect artifacts lacking extractable content or clear type
2.Log each with the reason it was skipped
3.Exclude rather than mis-tag
4.Queue scanned or empty exports for separate handling
5.Report coverage and freshness gaps
✓

The index stays trustworthy because uncertain artifacts are surfaced, not force-fit.

Integrations

CRM (Salesforce, HubSpot)
Knowledge Base / Vector Index
Google Workspace (Sheets, Drive)
Document Storage
Web Research & News

Industries

all

Built in Actava.ai

See it in action

A conversation that moves the work forward.

An agent at work

Illustrative example

Run the knowledge base ingest for this quarter's work.

Engagement Knowledge Base Builder

I've started the periodic run across the CRM and the knowledge store. It moves through three phases and ends with a count of processed artifacts and a list of any I couldn't classify.

Inputs for this run

  • CRM

    Notes, activities, workstreams, opportunities, accounts

  • Knowledge store

    Documents from the engagement corpus

Example complete

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Sample scenarios. Actions and outputs are illustrative.